R Notebook

What order does ISO standard follow? (e.g. year to second, second to year…) What is the minimum number of digits you can have in a year? Why is this? What clock system do the times use? How many time formats does ISO standard have? What timezone are time and dates automatically represented in? How are combined date-times represented?

Answer 1-Date and time values are ordered from the largest to smallest unit of time: year, month (or week), day, hour, minute, second, and fraction of second.

2-ISO 8601 prescribes, as a minimum, a four-digit year [YYYY]. This is to make sure that, for example, the year the year 1945 isn’t confused with the year 2045.

3-ISO 8601 uses the 24-hour clock system.

4-Four. You can have - hh:mm:ss.sss , hh:mm:ss, hh:mm, hh

5-Time zones are automatically represented in local time as UTC (coordinated universal time, GMT).

6-You use the letter T as a delimiter, e.g. “2007-04-05T14:30”

unclass(as.Date('2022-01-01'))

[1] 18993

posix = start at 1970-01-01 00:00:00

unclass(date_time1)

[1] 1577836800
attr(,"tzone")
[1] ""

date_time2 <- as.POSIXlt('2020-01-01 00:00:00')
date_time2

[1] "2020-01-01 GMT"

unclass(date_time2)

$sec
[1] 0

$min
[1] 0

$hour
[1] 0

$mday
[1] 1

$mon
[1] 0

$year
[1] 120

$wday
[1] 3

$yday
[1] 0

$isdst
[1] 0

$zone
[1] "GMT"

$gmtoff
[1] NA

date_time2$mday

[1] 1

library(tidyverse)

Registered S3 methods overwritten by 'dbplyr':
  method         from
  print.tbl_lazy     
  print.tbl_sql      
── Attaching packages ──────────────────────────────────── tidyverse 1.3.2 ──✔ ggplot2 3.3.6     ✔ purrr   0.3.4
✔ tibble  3.1.8     ✔ dplyr   1.0.9
✔ tidyr   1.2.0     ✔ stringr 1.4.0
✔ readr   2.1.2     ✔ forcats 0.5.1── Conflicts ─────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()

library(lubridate)

Attaching package: ‘lubridate’

The following objects are masked from ‘package:base’:

    date, intersect, setdiff, union

col type on r as: Date : ‘’ time: ‘’ date-time : ‘’

class(ymd('2019-01-19'))

[1] "Date"

mdy('January 9th, 2019')

[1] "2019-01-09"

dmy('9-Jan-2019')

[1] "2019-01-09"

ymd_hms('2019-01-19 10:08:26')

[1] "2019-01-19 10:08:26 UTC"

ymd_hm('2019-01-19 10:08')

[1] "2019-01-19 10:08:00 UTC"

ymd_h('2019-01-19 10')

[1] "2019-01-19 10:00:00 UTC"

netflix<- netflix %>% 
  mutate(date_added = mdy(date_added))
netflix

netflix<- netflix %>% 
  mutate(week_days = wday(date_added))

difftime: a dartetime obkect that represents days period: represent a timespan like week/ month/ day duration : represent an exact number of seconds

netflix <- netflix %>% 
  mutate(promo_date = date_added - weeks(2),
         removal_date = date_added + months(4))

netflix %>% 
  select(date_added, promo_date, removal_date)

as period can do “weeks/years”

duration gives seconds

ymd(20200110) + years(1)

[1] "2021-01-10"

ymd(20200110) + dyears(1)

[1] "2021-01-09 06:00:00 UTC"

##understanding timezone

Sys.timezone()

[1] "Europe/London"

OlsonNames()
#timezone names ^

ymd_hms('20230913 10:22:01', tz = "Atlantic/Faeroe")

[1] "2023-09-13 10:22:01 WEST"

 netflix %>%
  mutate(date_tz_1 = force_tz(date_added, tzone = 'Asia/Singapore'),
         date_tz_2 = with_tz(date_added, tzone = 'Asia/Singapore')) %>% 
  select(date_added, date_tz_1, date_tz_2)